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Generative Models and Statistical Validation
High Energy Physics - Phenomenology [Submitted on 28 May 2026] Title:Generative Models and Statistical Validation View PDF HTML (experimental)Abstract:Generative machine learning has become an essential tool in theoretical and experimental physics, especially in the context of fast surrogates and density estimators. In this work, we first introduce the underlying framework of modern generative networks and then discuss challenges in quantifying their accuracy, precision, and statistical power.
ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics
arXiv:2604.01313v2 Announce Type: replace-cross Abstract: High-fidelity simulations and complex inverse problems, such as detector modeling and unfolding, are computationally intensive bottlenecks across subatomic physics, yet essential for accurate physical interpretation. While Conditional Flow Matching (CFM) offers a robust acceleration approach, we demonstrate its standard training loss is fundamentally misleading. Specifically, utilizing a Jefferson Lab Nuclear Physics (NP) kinematic...
Generative Models and Statistical Validation
High Energy Physics - Phenomenology [Submitted on 28 May 2026] Title:Generative Models and Statistical Validation View PDF HTML (experimental)Abstract:Generative machine learning has become an essential tool in theoretical and experimental physics, especially in the context of fast surrogates and density estimators. In this work, we first introduce the underlying framework of modern generative networks and then discuss challenges in quantifying their accuracy, precision, and statistical power.
Castor: CERN Advanced STORage Manager
The CERN Advanced STORage manager (CASTOR) is a hierarchical storage (i.e. has disk and tape) management system which was developed at CERN for archiving physics data (with very large data volumes, see the plot on the right). Files can be stored, listed, retrieved and remotely accessed using CASTOR command-line tools or user applications that were developed using the CASTOR API. CASTOR provides a set of access protocols such as XROOT (the main and recommended protocol) and GridFTP.
SIGMA: A Versatile Streaming Graph Partitioner for Vertex- and Edge-Balanced Distributed GNN Training
Announce Type: new Abstract: Distributed Graph Neural Network (GNN) training depends critically on how the underlying graph is partitioned across compute resources. Existing graph partitioners focus either on vertex partitioning or edge partitioning and typically optimize only a single communication objective (edge cut or vertex cut) under a single balance constraint (vertex balance or edge balance).
ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics
arXiv:2604.01313v2 Announce Type: replace Abstract: High-fidelity simulations and complex inverse problems, such as detector modeling and unfolding, are computationally intensive bottlenecks across subatomic physics, yet essential for accurate physical interpretation. While Conditional Flow Matching (CFM) offers a robust acceleration approach, we demonstrate its standard training loss is fundamentally misleading. Specifically, utilizing a Jefferson Lab Nuclear Physics (NP) kinematic dataset...
Measurement of reactor neutrino oscillation with the first JUNO data
Abstract Neutrino oscillations (see refs. 1,2 and references therein), a quantum effect manifesting at macroscopic scales, are governed by lepton flavour mixing angles and neutrino mass-squared differences3 that are fundamental parameters of particle physics, representing phenomena beyond the Standard Model. Precision measurements of these parameters are essential for testing the completeness of the three-flavour framework, determining the mass ordering of neutrinos and probing possible new...